Propiedades psicométricas del Test de Montreal Cognitive Assessment: Moca-A y Moca-Basic en pacientes diabéticos, en un hospital de Lima, 2023
Bibliographic record
Abstract
La presente investigación va aplicar el Test de Montreal Cognitive Assessment (MoCA) en su versión original- Basic y adaptadas, en pacientes diabéticos, para evaluar el deterioro cognitivo. Objetivo: Evaluar las propiedades psicométricas: Confiabilidad y Validez del Test de cognición breve, Montreal Cognitive Assessment: MoCA-A y MoCA-Basic en pacientes diabéticos en un hospital de Lima. Metodología: Es una investigación Básica, enfoque cuantitativo, diseño no experimental de corte transversal simple, con muestreo no probabilístico por conveniencia. La muestra fue 357 pacientes diabéticos hospitalizados. El instrumento: Test Montreal Cognitive Assessment, versión MoCA-A original - adaptado y el MoCA-Basic original – adaptado. La prueba de confrontación el MMSE. Se utilizó el Programa estadístico de Jamobi y el Excel. Para la Confiabilidad: Coeficiente de estabilidad Test-Retest, coeficiente de equivalencia: ítem-test; en la consistencia interna el Coeficiente de Kuder Richardson 20. Para Validez concurrente y predictiva, el coeficiente de correlación de Pearson. Resultados: Altos valores de Confiabilidad y validez de criterio: concurrente y predictiva. El Test de MoCA tiene gran fortaleza: IC>95%. Sensibilidad > 0.88 y Especificidad> 0.96 Conclusiones: El test de MoCA-A y MoCA-B son confiables y válidos estadísticamente, pueden ser usados en diabetes mellitus y en población general, en el diagnóstico de deterioro cognitivo leve.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".